Resampled dimensional reduction for feature representation in machine learning
Systematic human learning by literature and data mining for feature selection in machine learning
Deep-insight visible neural network (DI-VNN) for improving interpretability of a non-image deep learning model by data-driven ontology
Human and machine learning pipelines for responsible clinical prediction using high-dimensional data
Data and script to reproduce the results presented in: Evaluation of the extraction of methodological study characteristics with JATSdecoder
CONIPHER: a computational framework for scalable phylogenetic reconstruction with error correction
Mapping cells to gene programs
Whole exome sequencing and RNA sequencing analyses of PDAC samples
Pre- and post-genotype filtration protocol to improve the variant imputation metrics with further quality control